Webinars

The hype around “the thinking sciences” — Artificial Intelligence, Machine Learning, and Data Science — is enormous, so it’s tempting to be skeptical of the return on investment claimed. Still, most of the results are real. The capabilities of Data Science, where models are inductively built from real history, have been growing steadily. I will reveal examples of the gains that can be achieved using five of our most interesting fielded solutions from the last two decades, from the diverse worlds of investment timing, credit scoring, drug discovery, medical diagnosis, and gas exploration.

Mitigating fraud is a complex problem and requires a comprehensive and flexible fraud analytics solution. Organizations can be anywhere along the broad spectrum of fraud analytics capabilities, from basic rules and reporting to complex network graph analysis. This webinar will show data science teams how to move to the next stage in the process, ultimately building out all of the components of a holistic and robust fraud analytics platform. At each stage, we will discuss technical details as well as problems to watch out for based on lessons learned over the years.

The most destructive fraudulent activity is not perpetrated by individual bad actors working alone, but by groups orchestrating fraud together. Comprehensive efforts in fraud analytics must consider how to use data to detect fraud rings, whether they relate to kickback schemes, money laundering, identity theft, or other coordinated crime. Even with limited data, approaching analytics from this angle can yield valuable insights into potential fraud that would have gone undetected with traditional methods.

This webinar will share best practices and lessons learned for developing and deploying effective fraud detection solutions based on extensive experience in both the commercial and federal government sectors.